In this video, I dive into a straightforward and easy-to-understand approach for predicting the closing price of the next candle in a trading context. Please note that this is a highly simplified model for educational purposes and doesn’t account for the many complexities of real-world trading. It’s a basic introduction to the concept of linear regression in the context of financial markets.
Key Points Covered:
We’ll explore a simplified linear regression model for predicting close prices.
You’ll learn how to calculate the price change per day (PCPD) and the average price change per day (Avg PCPD) from historical data.
We apply these calculations to make a simple prediction for the next candle’s closing price.
This video is perfect for beginners and those interested in understanding the basics of trading and predictive modeling. I will provide a clear explanations and visuals, including a step-by-step demonstration in Excel. Please remember that real-world trading involves a multitude of complex factors, and this model is for educational purposes only.
If you’re curious about the fundamentals of trading and want to learn about a simple approach to predicting close prices, this video is for you. Don’t forget to like, subscribe, and hit the notification bell to stay updated with more educational content on trading and finance.
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Disclaimer:
Any perspectives or opinions in this video are my own. I am not a financial adviser, so this is not financial advice. Any information and tools provided are for educational purposes only and do not constitute financial advice. The developers or the content creator are not liable for any investment decisions made based on any information received. It is the responsibility of the user to fully assess their risk tolerance and only trade with what they can afford to lose. Trading is risky, and past performance does not guarantee future results. You must agree that the use of any software discussed in this group should only be done on a demo account, and any advice given should be taken with caution. None of the members or admins are responsible for any trading losses.
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